Radar signal processing can be very computationally intensive. With the transition to digital techniques in general and high-resolution image formation in particular, computational requirements can easily grow to many millions of arithmetic operations. Indeed, such computational demands are limited only by the resolution required and, as might be expected, the desire to extract finer details is ever increasing.
To enhance cross-range resolution, that is, the ability to distinguish between two points next to each other at nearly the same distance from the radar receiver, a larger antenna can be used, but such an approach quickly becomes unwieldy for certain applications. For example, to observe meaningful details on the earth's surface from a relatively high altitude at non-exotic radar frequencies, an antenna kilometers in length might be required.
It was discovered that cross-range resolution could be enhanced by integrating multiple signals from a single target using a moving antenna (see U.S. Pat. No. 3,196,436), a technique now commonly referred to as synthetic aperture radar, or SAR. With SAR, a small antenna aboard an aircraft or spacecraft can be used to collect geographic data, often by side-looking, and a high resolution can be achieved independent of sensor altitude by synthesizing an extremely long antenna aperture using a signal processor.
The advantages of SAR are many, but it is not a technique that simplifies, as the reduction in physical antenna size results in a corresponding increase in computational intensity. To resolve and correct SAR data requires signal processing and analysis above and beyond the inherently complex operations associated with real-aperture digital radar. Like other high-resolution radar systems, SAR is coherent, in that it must retain both magnitude and phase of the backscattered echo signal. In addition, various processing techniques must be employed to sharpen the received beam, improve signal-to-noise ratio and, especially with SAR, to correct for radiometric and geometric distortions. In the digital domain, the filtering and other processes required to improve SAR image quality involve numerical operations such as Fourier transformation, correlation and convolution which, in turn, require numerous high-speed multiplications and/or additions of long data words.
Depending upon the requirements of the application, the computations required to implement various SAR algorithms may be performed on a variety of computer systems ranging from general-purpose machines, including supercomputers, to specialized array processors. However, resort to such physically large systems requires that the SAR problem be broken up, with pulse transmission and data collection being performed during flight but with the bulk of the signal processing being carried out in a separate ground station receiving the data via down-link. The need for a down-link increases equipment complexity and introduces communication problems of its own.
As such, for applications demanding processing throughputs in excess of those possible with general-purpose computer-based solutions, specialized hardware implementations have been developed to perform SAR-specific operations. Presently, however, even with such dedicated hardware, various modules are necessary to process each portion of the SAR algorithm, that is, to compute the requisite Fourier transformations, complex multiplications, and to form the modulus of the processed image. Additional hardware is typically required to implement resampling filters in each image dimension to correct for the geometric distortion.
Recently, several DSP devices have been introduced which provide more integrated solutions to the SAR processing problem. For example, an arithmetic element called the IQMAC, developed by United Technologies, implements a complex multiply-accumulate circuit which can be used as a building block in a SAR system, but the device requires substantial support circuitry in use. Similarly, a device manufactured by TRW Corp. and a two-chip set called the DaSP/PaC, originally developed by Honeywell Corporation, can perform fast Fourier transformations as well as complex and real multiplications, but these components also require additional hardware for less generic functions.
There remains, therefore, an unsatisfied need for a much more highly integrated solution, one that is dedicated to SAR signal processing and image formation. Such a device would forgo the need for unique module designs to implement each SAR processing operation and, as a consequence, dramatically increase the flexibility and performance of the overall system, decrease cost and streamline the logistical requirements of the resulting product. This will bring closer the ultimate goal of real-time image formation within a self-contained system aboard the same vehicle carrying the transmitter/receiver.